Results 41 to 50 of about 55,142 (282)

Skin Lesion Classification: A Deep Learning Approach with Local Interpretable Model-Agnostic Explanations (LIME) for Explainable Artificial Intelligence (XAI)

JOIV: International Journal on Informatics Visualization
The classification of skin cancer is crucial as the chance of survival increases significantly with timely and accurate treatment. Convolution Neural Networks (CNNs) have proven effective in classifying skin cancer. However, CNN models are often regarded
Sin Yi Hong, Lih Poh Lin
doaj   +1 more source

On the Capacity Region for Secure Index Coding

, 2018
We study the index coding problem in the presence of an eavesdropper, where the aim is to communicate without allowing the eavesdropper to learn any single message aside from the messages it may already know as side information.
Kim, Young-Han, Liu, Yuxin, Sadeghi, Parastoo, Vellambi, Badri N.   +3 more
core   +1 more source

Survey of XAI in Digital Pathology [PDF]

, 2020
Artificial intelligence (AI) has shown great promise for diagnostic imaging assessments. However, the application of AI to support medical diagnostics in clinical routine comes with many challenges. The algorithms should have high prediction accuracy but also be transparent, understandable and reliable.
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström   +2 more
openaire   +2 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Explainability and interpretability are important aspects in ensuring the security of decisions made by intelligent systems (review article)

Научно-технический вестник информационных технологий, механики и оптики
The issues of trust in decisions made (formed) by intelligent systems are becoming more and more relevant. A systematic review of Explicable Artificial Intelligence (XAI) methods and tools aimed at bridging the gap between the complexity of neural ...
D. N. Biryukov, A. S. Dudkin
doaj   +1 more source

On the stability of persistent entropy and new summary functions for Topological Data Analysis [PDF]

, 2018
Persistent entropy of persistence barcodes, which is based on the Shannon entropy, has been recently defined and successfully applied to different scenarios: characterization of the idiotypic immune network, detection of the transition between the ...
Atienza Martínez, María Nieves, González Díaz, Rocío, Soriano Trigueros, Manuel   +2 more
core  

Trustworthy XAI and Application

CoRR
Artificial Intelligence (AI) is an important part of our everyday lives. We use it in self-driving cars and smartphone assistants. People often call it a "black box" because its complex systems, especially deep neural networks, are hard to understand. This complexity raises concerns about accountability, bias, and fairness, even though AI can be quite ...
Nasim, MD Abdullah Al, Ferdous, A. S. M Anas, Rashid, Abdur, Soshi, Fatema Tuj Johura, Biswas, Parag, Biswas, Angona, Gupta, Kishor Datta   +6 more
openaire   +2 more sources

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Interpretable Ensemble-Based Intrusion Detection Using Feature Selection on the ToN_IoT Dataset

JISA (Jurnal Informatika dan Sains)
With With the rapid growth of IoT, securing interconnected devices against cyber threats has become critical. IoT datasets such as ToN-IoT are often high-dimensional, which poses challenges for efficient and accurate intrusion detection.
Vaman Shakir Sulaiman, Firas Mahmood Mustafa   +1 more
doaj   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source